Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px
init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
#load data
df = px.data.gapminder()
df.head()
| country | continent | year | lifeExp | pop | gdpPercap | iso_alpha | iso_num | |
|---|---|---|---|---|---|---|---|---|
| 0 | Afghanistan | Asia | 1952 | 28.801 | 8425333 | 779.445314 | AFG | 4 |
| 1 | Afghanistan | Asia | 1957 | 30.332 | 9240934 | 820.853030 | AFG | 4 |
| 2 | Afghanistan | Asia | 1962 | 31.997 | 10267083 | 853.100710 | AFG | 4 |
| 3 | Afghanistan | Asia | 1967 | 34.020 | 11537966 | 836.197138 | AFG | 4 |
| 4 | Afghanistan | Asia | 1972 | 36.088 | 13079460 | 739.981106 | AFG | 4 |
Recreate the barplot below that shows the population of different continents for the year 2007.
Hints:
# YOUR CODE HERE
#load data
df = px.data.gapminder()
df_2007 = df.query('year==2007')
fig = px.bar(df_2007, x="pop", y="continent", orientation='h')
fig.show()
df_2007 = df.query('year==2007')
df_2007_new = df_2007.groupby('continent').sum()
df_2007_new = df_2007_new.reset_index()
fig = px.bar(df_2007_new, y = 'continent', x = 'pop', color = 'continent', orientation = 'h',
color_discrete_map={
"Europe": "red",
"Asia": "green",
"Americas": "blue",
"Oceania": "goldenrod",
"Africa": "magenta"},
category_orders={'continent': ["Asia", "Africa", "Americas", "Europe", "Oceania"]}, text = 'pop',
title="Continents by population"
)
fig.show()
# YOUR CODE HERE
df_2007 = df.query('year==2007')
df_2007_new = df_2007.groupby('continent').sum()
df_2007_new = df_2007_new.reset_index()
fig = px.bar(df_2007_new, y = 'continent', x = 'pop', color = 'continent', orientation = 'h',
color_discrete_map={
"Europe": "red",
"Asia": "green",
"Americas": "blue",
"Oceania": "goldenrod",
"Africa": "magenta"},
category_orders={'continent': ["Asia", "Africa", "Americas", "Europe", "Oceania"]}, text = 'pop',
title="Continents by population"
)
fig.show()
Add text to each bar that represents the population
# YOUR CODE HERE
df_2007 = df.query('year==2007')
df_2007_new = df_2007.groupby('continent').sum()
df_2007_new = df_2007_new.reset_index()
fig = px.bar(df_2007_new, y = 'continent', x = 'pop', color = 'continent', orientation = 'h',
color_discrete_map={
"Europe": "red",
"Asia": "green",
"Americas": "blue",
"Oceania": "goldenrod",
"Africa": "magenta"},
category_orders={'continent': ["Asia", "Africa", "Americas", "Europe", "Oceania"]}, text = 'pop',
title="Continents by population"
)
fig.show()
Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years
# YOUR CODE HERE
# YOUR CODE HERE
df_grouped = df.groupby(['continent', 'year']).sum()
df_grouped = df_grouped.reset_index()
fig = px.bar(df_grouped, y="continent", x="pop", color="continent", orientation="h", hover_name = 'pop',
text = 'pop', animation_frame="year",
color_discrete_map={
"Europe": "red",
"Asia": "green",
"Americas": "blue",
"Oceania": "goldenrod",
"Africa": "magenta"},
category_orders={"continent": ["Asia", "Africa", "Americas", "Europe", "Oceania"]},
title="Question 4"
)
fig.update_xaxes(range=[0, 4000000000])
fig.show()
Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years
# YOUR CODE HERE
df_grouped = df.groupby(['country', 'year']).sum()
df_grouped = df_grouped.reset_index()
fig = px.bar(df_grouped, y="country", x="pop", color="country", orientation="h", hover_name = 'pop',
text = 'pop', animation_frame="year",
color_discrete_map={
"Europe": "red",
"Asia": "green",
"Americas": "blue",
"Oceania": "goldenrod",
"Africa": "magenta"},
category_orders={"continent": ["Asia", "Africa", "Americas", "Europe", "Oceania"]},
title="Question 4"
)
fig.update_xaxes(range=[0, 2000000000])
fig.update_layout(yaxis={'categoryorder':'total ascending'})
fig.show()
Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation
# YOUR CODE HERE
df_grouped = df.groupby(['country', 'year']).sum()
df_grouped = df_grouped.reset_index()
fig = px.bar(df_grouped, y="country", x="pop", color="country", orientation="h", hover_name = 'pop',
text = 'pop', animation_frame="year", height=1000,
color_discrete_map={
"Europe": "red",
"Asia": "green",
"Americas": "blue",
"Oceania": "goldenrod",
"Africa": "magenta"},
category_orders={"continent": ["Asia", "Africa", "Americas", "Europe", "Oceania"]},
title="Question 4"
)
fig.update_xaxes(range=[0, 2000000000])
fig.update_layout(yaxis={'categoryorder':'total ascending'})
fig.show()
# YOUR CODE HERE
df_grouped = df.groupby(['country', 'year']).sum()
df_grouped = df_grouped.reset_index()
fig = px.bar(df_grouped, y="country", x="pop", color="country", orientation="h", hover_name = 'pop',
text = 'pop', animation_frame="year",
color_discrete_map={
"Europe": "red",
"Asia": "green",
"Americas": "blue",
"Oceania": "goldenrod",
"Africa": "magenta"},
category_orders={"continent": ["Asia", "Africa", "Americas", "Europe", "Oceania"]},
title="Question 4"
)
fig.update_xaxes(range=[0, 2000000000])
fig.update_yaxes(range=(-.5, 9.5))
fig.update_layout(yaxis={'categoryorder':'total descending'})
fig.show()